lsm
===
Fast Python bindings for [SQLite's LSM key/value store](http://www.sqlite.org/src4/doc/trunk/www/lsmusr.wiki>).
The LSM storage engine was initially written as part of the experimental
SQLite4 rewrite (now abandoned). More recently, the LSM source code was moved
into the SQLite3 [source tree](https://www.sqlite.org/cgi/src/dir?ci=e148cdad35520e66&name=ext/lsm1)
and has seen some improvements and fixes. This project uses the LSM code from
the SQLite3 source tree.
Features:
* Embedded zero-conf database.
* Keys support in-order traversal using cursors.
* Transactional (including nested transactions).
* Single writer/multiple reader MVCC based transactional concurrency model.
* On-disk database stored in a single file.
* Data is durable in the face of application or power failure.
* Thread-safe.
* Releases GIL for read and write operations
(each connection has own mutex)
* Page compression (lz4 or zstd)
* Zero dependency static library
* Python 3.x.
Limitations:
The source for Python lsm is
[hosted on GitHub](https://github.com/mosquito/python-lsm).
If you encounter any bugs in the library, please
[open an issue](https://github.com/mosquito/python-lsm/issues/new),
including a description of the bug and any related traceback.
## Quick-start
Below is a sample interactive console session designed to show some of the
basic features and functionality of the ``lsm`` Python library.
To begin, instantiate a `LSM` object, specifying a path to a database file.
<!-- name: test_example_db -->
```python
from lsm import LSM
db = LSM('test.ldb')
assert db.open()
```
More pythonic variant is using context manager:
<!-- name: test_example_db_context_manager -->
```python
from lsm import LSM
with LSM("test.ldb") as db:
assert db.info()
```
Not opened database will raise a RuntimeError:
<!-- name: test_example_db -->
```python
import pytest
from lsm import LSM
db = LSM('test.ldb')
with pytest.raises(RuntimeError):
db.info()
```
### Binary/string mode
You should select mode for opening the database with ``binary: bool = True``
argument.
For example when you want to store strings just pass ``binary=False``:
<!-- name: test_binary_mode -->
```python
from lsm import LSM
with LSM("test_0.ldb", binary=False) as db:
# must be str for keys and values
db['foo'] = 'bar'
assert db['foo'] == "bar"
```
Otherwise, you must pass keys and values ad ``bytes`` (default behaviour):
<!-- name: test_string_mode -->
```python
from lsm import LSM
with LSM("test.ldb") as db:
db[b'foo'] = b'bar'
assert db[b'foo'] == b'bar'
```
### Key/Value Features
``lsm`` is a key/value store, and has a dictionary-like API:
<!-- name: test_getitem -->
```python
from lsm import LSM
with LSM("test.ldb", binary=False) as db:
db['foo'] = 'bar'
assert db['foo'] == 'bar'
```
Database apply changes as soon as possible:
<!-- name: test_get_del_item -->
```python
import pytest
from lsm import LSM
with LSM("test.ldb", binary=False) as db:
for i in range(4):
db[f'k{i}'] = str(i)
assert 'k3' in db
assert 'k4' not in db
del db['k3']
with pytest.raises(KeyError):
print(db['k3'])
```
By default, when you attempt to look up a key, ``lsm`` will search for an
exact match. You can also search for the closest key, if the specific key you
are searching for does not exist:
<!-- name: test_get_del_item_seek_mode -->
```python
import pytest
from lsm import LSM, SEEK_LE, SEEK_GE, SEEK_LEFAST
with LSM("test.ldb", binary=False) as db:
for i in range(4):
db[f'k{i}'] = str(i)
# Here we will match "k1".
assert db['k1xx', SEEK_LE] == '1'
# Here we will match "k1" but do not fetch a value
# In this case the value will always be ``True`` or there will
# be an exception if the key is not found
assert db['k1xx', SEEK_LEFAST] is True
with pytest.raises(KeyError):
print(db['000', SEEK_LEFAST])
# Here we will match "k2".
assert db['k1xx', SEEK_GE] == "2"
```
`LSM` supports other common dictionary methods such as:
* `keys()`
* `values()`
* `items()`
* `update()`
### Slices and Iteration
The database can be iterated through directly, or sliced. When you are slicing
the database the start and end keys need not exist -- ``lsm`` will find the
closest key (details can be found in the [LSM.fetch_range()](https://lsm-db.readthedocs.io/en/latest/api.html#lsm.LSM.fetch_range)
documentation).
<!--
name: test_slices;
-->
```python
from lsm import LSM
with LSM("test_slices.ldb", binary=False) as db:
# clean database
for key in db.keys():
del db[key]
db['foo'] = 'bar'
for i in range(3):
db[f'k{i}'] = str(i)
# Can easily iterate over the database items
assert (
sorted(item for item in db.items()) == [
('foo', 'bar'), ('k0', '0'), ('k1', '1'), ('k2', '2')
]
)
# However, you will not read the entire database into memory, as special
# iterator objects are used.
assert str(db['k0':'k99']).startswith("<lsm_slice object at")
# But you can cast it to the list for example
assert list(db['k0':'k99']) == [('k0', '0'), ('k1', '1'), ('k2', '2')]
```
You can use open-ended slices. If the lower- or upper-bound is outside the
range of keys an empty list is returned.
<!--
name: test_slices;
case: open_ended_slices
-->
```python
with LSM("test_slices.ldb", binary=False, readonly=True) as db:
assert list(db['k0':]) == [('k0', '0'), ('k1', '1'), ('k2', '2')]
assert list(db[:'k1']) == [('foo', 'bar'), ('k0', '0'), ('k1', '1')]
assert list(db[:'aaa']) == []
```
To retrieve keys in reverse order or stepping over more than one item,
simply use a third slice argument as usual.
Negative step value means reverse order, but first and second arguments
must be ordinarily ordered.
<!--
name: test_slices;
case: reverse_slices
-->
```python
with LSM("test_slices.ldb", binary=False, readonly=True) as db:
assert list(db['k0':'k99':2]) == [('k0', '0'), ('k2', '2')]
assert list(db['k0'::-1]) == [('k2', '2'), ('k1', '1'), ('k0', '0')]
assert list(db['k0'::-2]) == [('k2', '2'), ('k0', '0')]
assert list(db['k0'::3]) == [('k0', '0')]
```
You can also **delete** slices of keys, but note that delete **will not**
include the keys themselves:
<!--
name: test_slices;
case: del_slice
-->
```python
with LSM("test_slices.ldb", binary=False) as db:
del db['k0':'k99']
# Note that 'k0' still exists.
assert list(db.items()) == [('foo', 'bar'), ('k0', '0')]
```
### Cursors
While slicing may cover most use-cases, for finer-grained control you can use
cursors for traversing records.
<!--
name: test_cursors;
case: iterate_over_one_item
-->
```python
from lsm import LSM, SEEK_GE, SEEK_LE
with LSM("test_cursors.ldb", binary=False) as db:
del db["a":"z"]
db["spam"] = "spam"
with db.cursor() as cursor:
cursor.seek('spam')
key, value = cursor.retrieve()
assert key == 'spam'
assert value == 'spam'
```
Seeking over cursors:
<!--
name: test_cursors;
case: iterate_over_multiple_items
-->
```python
with LSM("test_cursors.ldb", binary=False) as db:
db.update({'k0': '0', 'k1': '1', 'k2': '2', 'k3': '3', 'foo': 'bar'})
with db.cursor() as cursor:
cursor.first()
key, value = cursor.retrieve()
assert key == "foo"
assert value == "bar"
cursor.last()
key, value = cursor.retrieve()
assert key == "spam"
assert value == "spam"
cursor.previous()
key, value = cursor.retrieve()
assert key == "k3"
assert value == "3"
```
Finding the first match that is greater than or equal to `'k0'` and move
forward until the key is less than `'k99'`
<!--
name: test_cursors;
case: iterate_ge_until_k99
-->
```python
with LSM("test_cursors.ldb", binary=False) as db:
with db.cursor() as cursor:
cursor.seek("k0", SEEK_GE)
results = []
while cursor.compare("k99") > 0:
key, value = cursor.retrieve()
results.append((key, value))
cursor.next()
assert results == [('k0', '0'), ('k1', '1'), ('k2', '2'), ('k3', '3')]
```
Finding the last match that is lower than or equal to `'k99'` and move
backward until the key is less than `'k0'`
<!--
name: test_cursors;
case: iterate_le_until_k0
-->
```python
with LSM("test_cursors.ldb", binary=False) as db:
with db.cursor() as cursor:
cursor.seek("k99", SEEK_LE)
results = []
while cursor.compare("k0") >= 0:
key, value = cursor.retrieve()
results.append((key, value))
cursor.previous()
assert results == [('k3', '3'), ('k2', '2'), ('k1', '1'), ('k0', '0')]
```
It is very important to close a cursor when you are through using it. For this
reason, it is recommended you use the `LSM.cursor()` context-manager, which
ensures the cursor is closed properly.
### Transactions
``lsm`` supports nested transactions. The simplest way to use transactions
is with the `LSM.transaction()` method, which returns a context-manager:
<!-- name: test_transactions -->
```python
from lsm import LSM
with LSM("test_tx.ldb", binary=False) as db:
del db["a":"z"]
for i in range(10):
db[f"k{i}"] = f"{i}"
with LSM("test_tx.ldb", binary=False) as db:
with db.transaction() as tx1:
db['k1'] = '1-mod'
with db.transaction() as tx2:
db['k2'] = '2-mod'
tx2.rollback()
assert db['k1'] == '1-mod'
assert db['k2'] == '2'
```
You can commit or roll-back transactions part-way through a wrapped block:
<!-- name: test_transactions_2 -->
```python
from lsm import LSM
with LSM("test_tx_2.ldb", binary=False) as db:
del db["a":"z"]
for i in range(10):
db[f"k{i}"] = f"{i}"
with LSM("test_tx_2.ldb", binary=False) as db:
with db.transaction() as txn:
db['k1'] = 'outer txn'
# The write operation is preserved.
txn.commit()
db['k1'] = 'outer txn-2'
with db.transaction() as txn2:
# This is committed after the block ends.
db['k1'] = 'inner-txn'
assert db['k1'] == "inner-txn"
# Rolls back both the changes from txn2 and the preceding write.
txn.rollback()
assert db['k1'] == 'outer txn', db['k1']
```
If you like, you can also explicitly call `LSM.begin()`, `LSM.commit()`, and
`LSM.rollback()`.
<!-- name: test_transactions_db -->
```python
from lsm import LSM
# fill db
with LSM("test_db_tx.ldb", binary=False) as db:
del db["k":"z"]
for i in range(10):
db[f"k{i}"] = f"{i}"
with LSM("test_db_tx.ldb", binary=False) as db:
# start transaction
db.begin()
db['k1'] = '1-mod'
# nested transaction
db.begin()
db['k2'] = '2-mod'
# rolling back nested transaction
db.rollback()
# comitting top-level transaction
db.commit()
assert db['k1'] == '1-mod'
assert db['k2'] == '2'
```
### Thanks to
* [@coleifer](https://github.com/coleifer) - this project was inspired by
[coleifer/python-lsm-db](https://github.com/coleifer/python-lsm-db).
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"author": "Dmitry Orlov",
"author_email": "me@mosquito.su",
"download_url": "https://files.pythonhosted.org/packages/06/6b/0ffe3ccab39dc87807aa52ddde66c7947324bbf1827604df571a44c5a64e/lsm-0.5.4.tar.gz",
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"description": "lsm\n===\n\nFast Python bindings for [SQLite's LSM key/value store](http://www.sqlite.org/src4/doc/trunk/www/lsmusr.wiki>).\nThe LSM storage engine was initially written as part of the experimental\nSQLite4 rewrite (now abandoned). More recently, the LSM source code was moved\ninto the SQLite3 [source tree](https://www.sqlite.org/cgi/src/dir?ci=e148cdad35520e66&name=ext/lsm1)\nand has seen some improvements and fixes. This project uses the LSM code from\nthe SQLite3 source tree.\n\nFeatures:\n\n* Embedded zero-conf database.\n* Keys support in-order traversal using cursors.\n* Transactional (including nested transactions).\n* Single writer/multiple reader MVCC based transactional concurrency model.\n* On-disk database stored in a single file.\n* Data is durable in the face of application or power failure.\n* Thread-safe.\n* Releases GIL for read and write operations\n (each connection has own mutex)\n* Page compression (lz4 or zstd)\n* Zero dependency static library\n* Python 3.x.\n\nLimitations:\n\nThe source for Python lsm is\n[hosted on GitHub](https://github.com/mosquito/python-lsm).\n\nIf you encounter any bugs in the library, please\n[open an issue](https://github.com/mosquito/python-lsm/issues/new),\nincluding a description of the bug and any related traceback.\n\n## Quick-start\n\nBelow is a sample interactive console session designed to show some of the\nbasic features and functionality of the ``lsm`` Python library.\n\nTo begin, instantiate a `LSM` object, specifying a path to a database file.\n\n<!-- name: test_example_db -->\n```python\nfrom lsm import LSM\ndb = LSM('test.ldb')\nassert db.open()\n```\n\nMore pythonic variant is using context manager:\n\n<!-- name: test_example_db_context_manager -->\n```python\nfrom lsm import LSM\nwith LSM(\"test.ldb\") as db:\n assert db.info()\n```\n\nNot opened database will raise a RuntimeError:\n\n<!-- name: test_example_db -->\n```python\nimport pytest\nfrom lsm import LSM\n\ndb = LSM('test.ldb')\n\nwith pytest.raises(RuntimeError):\n db.info()\n```\n\n### Binary/string mode\n\nYou should select mode for opening the database with ``binary: bool = True``\nargument.\n\nFor example when you want to store strings just pass ``binary=False``:\n\n<!-- name: test_binary_mode -->\n```python\nfrom lsm import LSM\nwith LSM(\"test_0.ldb\", binary=False) as db:\n # must be str for keys and values\n db['foo'] = 'bar'\n assert db['foo'] == \"bar\"\n```\n\nOtherwise, you must pass keys and values ad ``bytes`` (default behaviour):\n\n<!-- name: test_string_mode -->\n```python\nfrom lsm import LSM\n\nwith LSM(\"test.ldb\") as db:\n db[b'foo'] = b'bar'\n assert db[b'foo'] == b'bar'\n```\n\n### Key/Value Features\n\n``lsm`` is a key/value store, and has a dictionary-like API:\n\n<!-- name: test_getitem -->\n```python\nfrom lsm import LSM\nwith LSM(\"test.ldb\", binary=False) as db:\n db['foo'] = 'bar'\n assert db['foo'] == 'bar'\n```\n\nDatabase apply changes as soon as possible:\n\n<!-- name: test_get_del_item -->\n```python\nimport pytest\nfrom lsm import LSM\n\nwith LSM(\"test.ldb\", binary=False) as db:\n for i in range(4):\n db[f'k{i}'] = str(i)\n\n assert 'k3' in db\n assert 'k4' not in db\n del db['k3']\n\n with pytest.raises(KeyError):\n print(db['k3'])\n```\n\nBy default, when you attempt to look up a key, ``lsm`` will search for an\nexact match. You can also search for the closest key, if the specific key you\nare searching for does not exist:\n\n<!-- name: test_get_del_item_seek_mode -->\n```python\nimport pytest\nfrom lsm import LSM, SEEK_LE, SEEK_GE, SEEK_LEFAST\n\n\nwith LSM(\"test.ldb\", binary=False) as db:\n for i in range(4):\n db[f'k{i}'] = str(i)\n\n # Here we will match \"k1\".\n assert db['k1xx', SEEK_LE] == '1'\n\n # Here we will match \"k1\" but do not fetch a value\n # In this case the value will always be ``True`` or there will\n # be an exception if the key is not found\n assert db['k1xx', SEEK_LEFAST] is True\n\n with pytest.raises(KeyError):\n print(db['000', SEEK_LEFAST])\n\n # Here we will match \"k2\".\n assert db['k1xx', SEEK_GE] == \"2\"\n```\n\n`LSM` supports other common dictionary methods such as:\n\n* `keys()`\n* `values()`\n* `items()`\n* `update()`\n\n\n### Slices and Iteration\n\nThe database can be iterated through directly, or sliced. When you are slicing\nthe database the start and end keys need not exist -- ``lsm`` will find the\nclosest key (details can be found in the [LSM.fetch_range()](https://lsm-db.readthedocs.io/en/latest/api.html#lsm.LSM.fetch_range)\ndocumentation).\n\n<!--\n name: test_slices;\n-->\n```python\nfrom lsm import LSM\n\nwith LSM(\"test_slices.ldb\", binary=False) as db:\n\n # clean database\n for key in db.keys():\n del db[key]\n\n db['foo'] = 'bar'\n\n for i in range(3):\n db[f'k{i}'] = str(i)\n\n # Can easily iterate over the database items\n assert (\n sorted(item for item in db.items()) == [\n ('foo', 'bar'), ('k0', '0'), ('k1', '1'), ('k2', '2')\n ]\n )\n\n # However, you will not read the entire database into memory, as special\n # iterator objects are used.\n assert str(db['k0':'k99']).startswith(\"<lsm_slice object at\")\n\n # But you can cast it to the list for example\n assert list(db['k0':'k99']) == [('k0', '0'), ('k1', '1'), ('k2', '2')]\n```\n\nYou can use open-ended slices. If the lower- or upper-bound is outside the\nrange of keys an empty list is returned.\n\n\n<!--\n name: test_slices;\n case: open_ended_slices\n-->\n```python\nwith LSM(\"test_slices.ldb\", binary=False, readonly=True) as db:\n assert list(db['k0':]) == [('k0', '0'), ('k1', '1'), ('k2', '2')]\n assert list(db[:'k1']) == [('foo', 'bar'), ('k0', '0'), ('k1', '1')]\n assert list(db[:'aaa']) == []\n```\n\nTo retrieve keys in reverse order or stepping over more than one item,\nsimply use a third slice argument as usual.\nNegative step value means reverse order, but first and second arguments\nmust be ordinarily ordered.\n\n<!--\n name: test_slices;\n case: reverse_slices\n-->\n```python\nwith LSM(\"test_slices.ldb\", binary=False, readonly=True) as db:\n assert list(db['k0':'k99':2]) == [('k0', '0'), ('k2', '2')]\n assert list(db['k0'::-1]) == [('k2', '2'), ('k1', '1'), ('k0', '0')]\n assert list(db['k0'::-2]) == [('k2', '2'), ('k0', '0')]\n assert list(db['k0'::3]) == [('k0', '0')]\n```\n\nYou can also **delete** slices of keys, but note that delete **will not**\ninclude the keys themselves:\n\n<!--\n name: test_slices;\n case: del_slice\n-->\n```python\nwith LSM(\"test_slices.ldb\", binary=False) as db:\n del db['k0':'k99']\n\n # Note that 'k0' still exists.\n assert list(db.items()) == [('foo', 'bar'), ('k0', '0')]\n```\n\n### Cursors\n\nWhile slicing may cover most use-cases, for finer-grained control you can use\ncursors for traversing records.\n\n<!--\n name: test_cursors;\n case: iterate_over_one_item\n-->\n```python\nfrom lsm import LSM, SEEK_GE, SEEK_LE\n\nwith LSM(\"test_cursors.ldb\", binary=False) as db:\n del db[\"a\":\"z\"]\n\n db[\"spam\"] = \"spam\"\n\n with db.cursor() as cursor:\n cursor.seek('spam')\n key, value = cursor.retrieve()\n assert key == 'spam'\n assert value == 'spam'\n```\n\nSeeking over cursors:\n\n<!--\n name: test_cursors;\n case: iterate_over_multiple_items\n-->\n```python\nwith LSM(\"test_cursors.ldb\", binary=False) as db:\n db.update({'k0': '0', 'k1': '1', 'k2': '2', 'k3': '3', 'foo': 'bar'})\n\n with db.cursor() as cursor:\n\n cursor.first()\n key, value = cursor.retrieve()\n assert key == \"foo\"\n assert value == \"bar\"\n\n cursor.last()\n key, value = cursor.retrieve()\n assert key == \"spam\"\n assert value == \"spam\"\n\n cursor.previous()\n key, value = cursor.retrieve()\n assert key == \"k3\"\n assert value == \"3\"\n\n```\n\nFinding the first match that is greater than or equal to `'k0'` and move\nforward until the key is less than `'k99'`\n\n<!--\n name: test_cursors;\n case: iterate_ge_until_k99\n-->\n```python\nwith LSM(\"test_cursors.ldb\", binary=False) as db:\n with db.cursor() as cursor:\n cursor.seek(\"k0\", SEEK_GE)\n results = []\n\n while cursor.compare(\"k99\") > 0:\n key, value = cursor.retrieve()\n results.append((key, value))\n cursor.next()\n\n assert results == [('k0', '0'), ('k1', '1'), ('k2', '2'), ('k3', '3')]\n\n```\n\nFinding the last match that is lower than or equal to `'k99'` and move\nbackward until the key is less than `'k0'`\n\n<!--\n name: test_cursors;\n case: iterate_le_until_k0\n-->\n```python\nwith LSM(\"test_cursors.ldb\", binary=False) as db:\n with db.cursor() as cursor:\n cursor.seek(\"k99\", SEEK_LE)\n results = []\n\n while cursor.compare(\"k0\") >= 0:\n key, value = cursor.retrieve()\n results.append((key, value))\n cursor.previous()\n\n assert results == [('k3', '3'), ('k2', '2'), ('k1', '1'), ('k0', '0')]\n```\n\nIt is very important to close a cursor when you are through using it. For this\nreason, it is recommended you use the `LSM.cursor()` context-manager, which\nensures the cursor is closed properly.\n\n### Transactions\n\n``lsm`` supports nested transactions. The simplest way to use transactions\nis with the `LSM.transaction()` method, which returns a context-manager:\n\n<!-- name: test_transactions -->\n```python\nfrom lsm import LSM\n\nwith LSM(\"test_tx.ldb\", binary=False) as db:\n del db[\"a\":\"z\"]\n for i in range(10):\n db[f\"k{i}\"] = f\"{i}\"\n\n\nwith LSM(\"test_tx.ldb\", binary=False) as db:\n with db.transaction() as tx1:\n db['k1'] = '1-mod'\n\n with db.transaction() as tx2:\n db['k2'] = '2-mod'\n tx2.rollback()\n\n assert db['k1'] == '1-mod'\n assert db['k2'] == '2'\n```\n\nYou can commit or roll-back transactions part-way through a wrapped block:\n\n<!-- name: test_transactions_2 -->\n```python\nfrom lsm import LSM\n\nwith LSM(\"test_tx_2.ldb\", binary=False) as db:\n del db[\"a\":\"z\"]\n for i in range(10):\n db[f\"k{i}\"] = f\"{i}\"\n\nwith LSM(\"test_tx_2.ldb\", binary=False) as db:\n with db.transaction() as txn:\n db['k1'] = 'outer txn'\n\n # The write operation is preserved.\n txn.commit()\n\n db['k1'] = 'outer txn-2'\n\n with db.transaction() as txn2:\n # This is committed after the block ends.\n db['k1'] = 'inner-txn'\n\n assert db['k1'] == \"inner-txn\"\n\n # Rolls back both the changes from txn2 and the preceding write.\n txn.rollback()\n\n assert db['k1'] == 'outer txn', db['k1']\n```\n\n\nIf you like, you can also explicitly call `LSM.begin()`, `LSM.commit()`, and\n`LSM.rollback()`.\n\n<!-- name: test_transactions_db -->\n```python\nfrom lsm import LSM\n\n# fill db\nwith LSM(\"test_db_tx.ldb\", binary=False) as db:\n del db[\"k\":\"z\"]\n for i in range(10):\n db[f\"k{i}\"] = f\"{i}\"\n\n\nwith LSM(\"test_db_tx.ldb\", binary=False) as db:\n # start transaction\n db.begin()\n db['k1'] = '1-mod'\n\n # nested transaction\n db.begin()\n db['k2'] = '2-mod'\n # rolling back nested transaction\n db.rollback()\n\n # comitting top-level transaction\n db.commit()\n\n assert db['k1'] == '1-mod'\n assert db['k2'] == '2'\n```\n\n### Thanks to\n\n* [@coleifer](https://github.com/coleifer) - this project was inspired by\n[coleifer/python-lsm-db](https://github.com/coleifer/python-lsm-db).\n\n\n",
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